If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
To Olley, machine learning fills a gap in technology that has existed for a long time: solving complex problems with pattern recognition. "With the majority of Elsevier's revenue coming from technology-based products and services, we started using machine learning in our commercial products, but it's equally applicable to internal IT platforms," Olley says. As part of the executive teams within RBI and Elsevier, Dan continues to drive organic online product growth across the portfolio. Prior to RELX Group, Dan held technology and product management leadership roles with GM Financial, Wunderman Cato Johnson, and IBM, as well as a number of software organizations in the United Kingdom and other international locales.
"We invented a computing model called GPU accelerated computing and we introduced it almost slightly over 10 years ago," Huang said, noting that while AI is only recently dominating tech news headlines, the company was working on the foundation long before that. Nvidia's tech now resides in many of the world's most powerful supercomputers, and the applications include fields that were once considered beyond the realm of modern computing capabilities. Now, Nvidia's graphics hardware occupies a more pivotal role, according to Huang – and the company's long list of high-profile partners, including Microsoft, Facebook and others, bears him out. GTC, in other words, has evolved into arguably the biggest developer event focused on artificial intelligence in the world.
According to the IBM Institute for Business Value the market will see a rapid adoption of initial cognitive systems. The most likely candidates have moved beyond descriptive and diagnostic, predictive and routine industry-specific capabilities. In fact, the widespread adoption of cognitive systems and artificial intelligence (AI) across various industries is expected to drive worldwide revenues from nearly US$8.0 billion in 2016 to more than US$47 billion in 2020. The analyst firm IDC predicts that the banking, retail, healthcare and discrete manufacturing industries will generate more than 50% of all worldwide cognitive/ AI revenues in 2016. Banking and retail will each deliver nearly US$1.5 billion, while healthcare and discrete manufacturing will deliver the greatest revenue growth over the 2016-2020 forecast period, with CAGRs of 69.3% and 61.4%, respectively.
As our desktop computers, laptops, mobile devices, etc. stand idly by for a huge portion of the day, the need for computing resources is growing at a fast pace. Large IoT ecosystems, machine learning and deep learning algorithms and other sophisticated solutions being deployed in every domain and industry are raising the demand for stronger cloud servers and more bandwidth to address the minute needs of enterprises and businesses. So how can we make a more economic and efficient use of all the computing power that's going to waste? Blockchain, the distributed ledger that's gaining traction across various domains, might have the answer to the dilemma by providing a platform that enables participants to lend and borrow computing resources -- and make money in the process. "There is a growing demand for computing power from industries and scientific communities to run large applications and process huge volumes of data," says Gilles Fedak, co-founder of iEx.ec, a distributed cloud computing platform.
According to the IBM Institute for Business Value the market will see a rapid adoption of initial cognitive systems. The most likely candidates have moved beyond descriptive and diagnostic, predictive and routine industry-specific capabilities. Seventy percent of survey respondents are currently using advanced programmatic analytics in three or more departments. In fact, the widespread adoption of cognitive systems and artificial intelligence (AI) across various industries is expected to drive worldwide revenues from nearly US$8.0 billion in 2016 to more than US$47 billion in 2020. The analyst firm IDC predictsthat the banking, retail, healthcare and discrete manufacturing industries will generate more than 50% of all worldwide cognitive/ AI revenues in 2016. Banking and retail will each deliver nearly US$1.5 billion, while healthcare and discrete manufacturing will deliver the greatest revenue growth over the 2016-2020 forecast period, with CAGRs of 69.3% and 61.4%, respectively.
For many years I have been part of discussions about how to diversify computing, particularly about how we recruit and retain a more diverse cohort of computer science (CS) students. I wholeheartedly support this goal, and spend a considerable amount of my effort as chair of ACM-W helping to drive programs that focus on one aspect of this diversification, namely encouraging women students to stay in computing. Of late I have become very concerned about how some elements of the diversity argument are being expressed and then implemented in teaching practices. Problem 1. Women are motivated by social relevance, so when we teach them we have to discuss ways in which computing can contribute to the social good. Problem 2. Students from underrepresented minorities (URM) respond to culturally relevant examples, so when we teach them we have to incorporate these examples into course content.
December 14, 2016 – New York & London – DataArt, a leading global technology consultancy, predicts that 2017 will be a year of integration, disruption and transformation due in large part to the digitalization of key industry sectors. Cyber security and data protection will become major board-level concerns as financial institutions realize that failing to protect customer information will be their biggest source of regulatory non-compliance and reputational risk. Organizations will invest heavily in correcting technology vulnerabilities, lax cultures and poor processes. As a result, data management in all its forms will dominate 2017. Rapid digitalization of customer-facing services will be a matter of organizational life and death as e-commerce and fintech elevate expectations for the optimal user experience (UX).
Although AI hasn't yet taken off in the enterprise market, it soon may. AI could be used to enhance customer service, provide companies with recommendations based on data analytics, root out fraud or help manufacturers find defects in products before they're shipped. The market for AI in the business world is going to heat up, according to research firm IDC, which predicts that the market for cognitively enabled applications and software is going to be worth $40 billion in 2020. One kind of AI that has gotten a lot of attention lately is machine learning, an artificial intelligence that can learn from and make predictions based on data it accesses. Google is building the technology into the company's cloud product in hopes of winning enterprise business.
Amazon.com Inc. introduced an image recognition program, a speech-to-text service dubbed Polly, and tools for building conversational apps, highlighting its push to add artificial intelligence to its cloud-computer offerings. Andy Jassy, chief executive officer of the Amazon Web Services unit, unveiled the new products Wednesday at the company's fifth annual re:Invent conference, which drew 32,000 people from diverse industries to Las Vegas. He pitched Amazon's wide breadth of services and ability to customize them for clients, while poking fun at competitor Oracle Corp., which Amazon dismisses as a cloud pretender. The event attracted people from financial services, health care, gaming and other industries interested in learning more about how to use cloud computing, and let Amazon flex its muscles as a market leader in the fast-growing industry. Public cloud spending is expected to increase almost 17 percent to $204 billion this year, according to researcher Gartner Inc. Amazon is trying to maintain its lead over Microsoft Corp., Alphabet Inc.'s Google, IBM and Oracle as more companies transition from using their servers to renting computing power and data space hosted remotely, which they access via the internet.